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Home / Admissions / PhD Programme in Statistics 2019 @ University of Calcutta, Kolkata

PhD Programme in Statistics 2019 @ University of Calcutta, Kolkata

Adminissions Eligibility:
Candidates with M.Sc. or equivalent degree in Statistics and allied subjects from any UGC recognized University/Institute with 55% marks in aggregate (SC /ST/OBC with 50% marks) are eligible to apply for admission to the PhD programme.
(a) In case of candidates from other Universities, admission for the PhD Programme will proceed after determination of equivalence by the relevant University body and fulfillment of the admission criteria.
(b) Foreign students will be required to produce clearance from the government of India and/or other appropriate authorities, if any, for admission to the PhD Programme.
Enrolment in the PhD Programme may be allowed to only such foreign nationals as have obtained and are holding research visa.
(c) The non-creamy layer certificate would have to be submitted by OBC candidates.
3. The admission procedure consists of a written test followed by an interview for candidates successful in the same. Those who have cleared UGC/CSIR (JRF) examinations/ NET / SET (Mathematical Sciences) / GATE (Mathematics) or hold DST INSPIRE Fellowship/ Teachers’ Fellowship or have obtained M. Phil. degree in Statistics and allied subjects or M. Tech. (QR&OR) degree of ISI prior to the application deadline will be exempted from the written examination but will have to appear in the interview.

How to apply:
Application forms may be downloaded from the university website,
(http://www.caluniv.ac.in/admission/CU_RET_Form.pdf ).

Important dates:

  • Last date: 20th August, 2019.
  • Date of common written test: 04th September, 2019 (12 noon – 3 p.m.)
  • Result of common written test: 12th September, 2019.
  • Date of Interview: 19th September, 2019 (from 12 noon).
  • Date of publication of selection list: 26th September, 2019.

For more details, please visit, https://www.caluniv.ac.in/  or
https://www.caluniv.ac.in/admission/stat-Phd-18-7-19.pdf  

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